Tales From Decrypt
Jun. 4th, 2010 05:04 pm![[personal profile]](https://www.dreamwidth.org/img/silk/identity/user.png){kind=small}
rinueI'm good at math, but I don't have a mathematical mind; I'm a code breaker, not a number theorist. I mean, I'll derive the hell out of your curves, but I'm not really interested in generating my own model. Statistic/econonometric literate, not authorial. I debug; I don't program. I enjoy accounting from a logic puzzle standpoint, but as an auditor I think double entry is stupid.
Point being it is very easy for me to work out the right answer to an equation, but that's not connected to knowing what the equation means. (I hated geometric proofs.) Somebody has to tell me, or I'm probably not going to find out; I have neither the intuition nor the compulsion to know.
By the time I left calculus, I was on higher level stuff called LaPlace transforms. I studied engineering, remember. I knew they had something to do with electricity because they were in the electrical engineering department. But really the variables could have been anything.
Yesterday, I was captioning a FERC conference, and they were talking about stochastic models to estimate the unit cost in a variable power system -- one in which, say, your electrical grid includes a wind farm. We don't have the computational power yet to forecast weather with enough granularity to be sure of how much power we're going to get out of that wind farm on a given day, and we need to be able to guess whether we can take a unit offline for maintenance, and how much to charge customers, and how much energy to reserve and all kinds of stuff we just don't have to worry about with a nuclear plant. So this is the big thing right now and a lot of mathematicians and physicists are working on it. It's exciting.
While they were describing the new stochastic models they're working on, they compared them to older methods we've traditionally used . . . and it dawned on me they were talking LaPlace. It was/is a method of modeling a variable system and using that to describe a range of possible data outcomes. I think. That's what it is.
As an analogy for English majors, this is like spending years thinking that . . . I don't know. It's not really like anything. It's like the five year gap between when I started multiplying matrixes by each other and when I figured out they were coordinates and velocities. I feel very satisfied. It is like being the guy who broke PURPLE but didn't know Japanese, if someone then read him the translated telegram. I never needed to know -- that was never the point for me -- but it sure is satisfying.
In other news, a trip to the periodontist has added another tool to my arsenal, which now means I use no fewer than five seperate utensils each night (sometimes as many as seven) applying to my teeth, three of which are different specialized brushes. Also, my toothpaste is prescription. My teeth are frickin' diva.
Point being it is very easy for me to work out the right answer to an equation, but that's not connected to knowing what the equation means. (I hated geometric proofs.) Somebody has to tell me, or I'm probably not going to find out; I have neither the intuition nor the compulsion to know.
By the time I left calculus, I was on higher level stuff called LaPlace transforms. I studied engineering, remember. I knew they had something to do with electricity because they were in the electrical engineering department. But really the variables could have been anything.
Yesterday, I was captioning a FERC conference, and they were talking about stochastic models to estimate the unit cost in a variable power system -- one in which, say, your electrical grid includes a wind farm. We don't have the computational power yet to forecast weather with enough granularity to be sure of how much power we're going to get out of that wind farm on a given day, and we need to be able to guess whether we can take a unit offline for maintenance, and how much to charge customers, and how much energy to reserve and all kinds of stuff we just don't have to worry about with a nuclear plant. So this is the big thing right now and a lot of mathematicians and physicists are working on it. It's exciting.
While they were describing the new stochastic models they're working on, they compared them to older methods we've traditionally used . . . and it dawned on me they were talking LaPlace. It was/is a method of modeling a variable system and using that to describe a range of possible data outcomes. I think. That's what it is.
As an analogy for English majors, this is like spending years thinking that . . . I don't know. It's not really like anything. It's like the five year gap between when I started multiplying matrixes by each other and when I figured out they were coordinates and velocities. I feel very satisfied. It is like being the guy who broke PURPLE but didn't know Japanese, if someone then read him the translated telegram. I never needed to know -- that was never the point for me -- but it sure is satisfying.
In other news, a trip to the periodontist has added another tool to my arsenal, which now means I use no fewer than five seperate utensils each night (sometimes as many as seven) applying to my teeth, three of which are different specialized brushes. Also, my toothpaste is prescription. My teeth are frickin' diva.
